Pb-Free Alloy Silver Content and Thermal Fatigue Reliability of a Large Plastic Ball Grid Array (PBGA) Package
Bibliographic record
Abstract
ABSTRACT This paper presents the latest results from an on-going investigation of Pb-free solder joint microstructure and attachment reliability of a 680 I/O plastic ball grid array (PBGA). Previously published work compared the temperature cycling performance of Sn4.0Ag0.5Cu (SAC405) and SnPb solder assemblies as a function of dwell time using an IPC-9701 accelerated temperature cycling test (ATC). In the current study, the accelerated temperature cycling matrix is expanded to include two additional Pb-free alloys, SAC305 (3% Ag) and SAC105 (1% Ag). The SAC305 and SAC105 BGA components were assembled and tested using either a dissimilar SAC405 paste or a matching solder paste such as SAC305 ball with SAC305 paste. As in the previously published studies, the 0°C to 100°C accelerated temperature cycling (ATC) tests were conducted using 10, 30, and 60 minute dwell times. The test results show that the thermal fatigue performance improved substantially with a higher Ag content BGA alloy. Surprisingly, assembly with the higher Ag solder paste resulted in a measureable though small increase in thermal fatigue performance of both the SAC305 ands SAC105. The characteristic fatigue lifetime was inversely proportional to the test dwell time, which is consistent with previously published findings on this BGA package as well as SAC solders in general.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".